Original listing text, shown exactly as published by the company.
What you’ll do
- Build and own the PMM knowledge harness. Design and maintain the structured knowledge base that grounds every agent output: product capabilities, vertical positioning, competitive intelligence, customer proof points, and buyer personas, organized so agents can retrieve and reason over them accurately. This is not a document library. It is the retrieval layer your agents run on. The quality of what gets indexed here, how it's structured, chunked, and kept current, determines the quality of everything the system produces. Every customer conversation, competitive insight, and product update you feed into it makes every future output more accurate and more useful.
- Build, deploy, and iterate on AI agents that produce PMM outputs. Design the agent workflows that generate messaging frameworks, battlecards, one-pagers, decks, email sequences, and enablement materials directly from the knowledge base. Own the full stack: prompt architecture, retrieval logic, output templates, and the feedback loops that improve agent performance over time. The goal is PMM-quality assets available to any team in the org, on demand, without a queue.
- Own editorial quality and system trust. Review and refine agent-generated outputs before they reach the teams that use them. Your judgment is what separates a system that produces volume from one that produces work worth using, especially for buyers who read carefully and will notice when we are not specific. As agent output quality improves and trust builds, this layer gets lighter; in the near term it is a critical part of the role.
- Run the internal PMM service layer. Field asset requests from sales, CS, partnerships, and pipeline marketing. Route finished agent outputs to the teams that need them. Maintain the feedback loops that surface knowledge gaps, flag agent errors, and tell you what the system is consistently getting wrong. Every team in the org should experience PMM as a fast, high-quality service.
- Measure and improve system performance. Define and track the metrics that tell you whether the system is working, including feedback from sellers, asset utilization, and win rates by segment and vertical. Use that data to set priorities and make the case for investment.
Qualifications
- A product marketing foundation, with several years of B2B marketing experience. You understand how product marketing works with cross functional partners, and how to systematize the work of this function.
- Genuine AI fluency, not theoretical. You have built workflows using LLMs, agents, or AI automation tools in a real marketing context. You have thought through where AI accelerates work worth accelerating and where human judgment is the thing that actually matters. You are not learning this on the job.
- Editorial judgment. You can tell the difference between an output that sounds right and one that reflects how a sophisticated buyer actually thinks about their problem. You hold the system's output to the same standard you'd hold your own writing.
- Operational rigor. You are comfortable building and maintaining systems, not just producing assets. You can think in workflows, identify where a process is breaking down, and fix it without waiting for someone else to tell you it's a problem.
- Experience in financial services, fintech, or complex enterprise SaaS is strongly preferred. Familiarity with fund operations, investor relations, or private markets workflows is a meaningful advantage. You do not need to be a fund accountant, but you should be able to learn the domain quickly and take it seriously.
- A genuine partnership mentality. You understand that the system you're building serves the whole org, and that means building trust with sales, CS, partnerships, and product, not just delivering outputs into a void. People across the organization should want to contribute to the knowledge base because working with you makes it worth their time.
- Comfort with a role that doesn't have a clean precedent. This is not a role with an established playbook. The person in it should find that energizing rather than unsettling
CompensationCompensation for this position includes a base salary, equity, and a variety of benefits. The U.S. base salary range for this role is $160,000 - $215,000. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.
